Nano-H: The World's First h_model

Nano-H is a revolutionary, ultra-minimalist language model architecture. While the industry trends toward trillion-parameter behemoths, Nano-H proves that with just 2 trainable parameters, you can achieve 100% precision, 100% recall, and 0% hallucination for the most important character in the alphabet: H.

Key Features

  • Architecture: h_model
  • Parameter Count: 2
  • Vocabulary Size: 1 ("H")
  • Inference Latency: Measured in nanoseconds

Benchmarks

Benchmark Nano-H Score
Output Consistency 100%
H-Accuracy 100%

Usage

To experience the definitive power of the h_model architecture, load it with trust_remote_code=True:

from transformers import AutoModel, AutoTokenizer

model_path = "Fu01978/Nano-H"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModel.from_pretrained(model_path, trust_remote_code=True)

inputs = tokenizer("Hello?", return_tensors="pt")
outputs = model.generate(inputs["input_ids"], max_length=1)
print(tokenizer.decode(outputs[0]))

Safety & Alignment

Nano-H is inherently safe. It cannot be jailbroken to provide instructions for dangerous activities, as any such request will be met with a singular "H".

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Safetensors
Model size
2 params
Tensor type
F32
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